University of Sistan and Baluchestan Journal of Natural Environmental Hazards 2676-4377 Articles in Press 2025 12 31 Darab Watershed, Flood, Data Mining, Maximum Entropy. Darab Watershed, Flood, Data Mining, Maximum Entropy. 1 1 9662 10.22111/jneh.2025.52982.2136 FA Reza Zakerinejad Assistant Professor, Faculty of Geographical Sciences and Planning, University of Isfahan, Isfahan, Iran Zahra Ostad Hosseini Master of Remote Sensing and Geographic Information Systems, University of Isfahan, Iran Yasmin Ghobishawi Master of Remote Sensing and Geographic Information Systems, University of Isfahan, Iran Journal Article 2025 08 19 Floods are among the most significant natural hazards, causing severe damage to lives, property, and the environment annually. The Darab watershed in Fars province, due to its specific climatic conditions, topography, and geological structure, is recognized as one of the areas at high risk of flooding. This study aims to prepare of flood risk map by using the Maximum Entropy (MaxEnt) model and analyze the factors influencing floods in the studied watershed. This is a quantitative and applied research that uses field and available data, focusing on areas with high flood risk. By utilizing data mining techniques, GIS, and remote sensing images, flood risk areas are classified. Various environmental and topographic factors were used as independent variables, including 19 environmental parameters such as precipitation, land slope, soil type, drainage density, land use, and moisture, and topographic indices and etc. These data were collected from reliable sources such as satellite imagery, Digital Elevation Models (DEM), meteorological stations, and geological maps. After data preprocessing, the models were run, and their accuracy was evaluated. Finally, the flood susceptibility map was validated using AUC, and high-risk areas were identified. Preparation of the flood risk map shows that approximately 20% of the Darab watershed is at high risk, especially in low-lying areas with poor vegetation and inappropriate land use. It was also determined that variables such as precipitation, distance from stream, and elevation have the most significant impact on flood occurrence. The results indicate that the MaxEnt model has acceptable capability in predicting high-risk areas and can play an effective role in crisis management and regional planning. Floods are among the most significant natural hazards, causing severe damage to lives, property, and the environment annually. The Darab watershed in Fars province, due to its specific climatic conditions, topography, and geological structure, is recognized as one of the areas at high risk of flooding. This study aims to prepare of flood risk map by using the Maximum Entropy (MaxEnt) model and analyze the factors influencing floods in the studied watershed. This is a quantitative and applied research that uses field and available data, focusing on areas with high flood risk. By utilizing data mining techniques, GIS, and remote sensing images, flood risk areas are classified. Various environmental and topographic factors were used as independent variables, including 19 environmental parameters such as precipitation, land slope, soil type, drainage density, land use, and moisture, and topographic indices and etc. These data were collected from reliable sources such as satellite imagery, Digital Elevation Models (DEM), meteorological stations, and geological maps. After data preprocessing, the models were run, and their accuracy was evaluated. Finally, the flood susceptibility map was validated using AUC, and high-risk areas were identified. Preparation of the flood risk map shows that approximately 20% of the Darab watershed is at high risk, especially in low-lying areas with poor vegetation and inappropriate land use. It was also determined that variables such as precipitation, distance from stream, and elevation have the most significant impact on flood occurrence. The results indicate that the MaxEnt model has acceptable capability in predicting high-risk areas and can play an effective role in crisis management and regional planning. https://jneh.usb.ac.ir/article_9662_b2e93bf6e84f7527bb5fe69b44f591d9.pdf